“…Flynn et al (2018), in a review of 10 studies, found the strongest evidence about predictors of Active Support was in respect to training (classroom combined with in-situ methods), relatively low staff-to-service user ratios and larger services (maximum of six service users), and management processes, such as team meetings. More recently, a large Australian study that applied multilevel modelling found predictors of good Active Support were the individuals' adaptive behaviour, strength of frontline practice leadership, staff training in Active Support, and time since Active Support was implemented (Bigby, Bould, Iacono, Kavangh, & Beadle-Brown, 2019a). Similar predictors were found in a study of increases in the quality of Active Support over time, which included repeated measures from the same 51 services in eight organisations over periods of two to seven years (Bould, Bigby, Iacono, & Beadle-Brown, 2019).…”